{"total":63,"rows":[{"id":"2209.03430","title":"Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions","created":"2022-09-07","cited_by_count":116,"area":null},{"id":"2209.07118","title":"Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge","created":"2022-09-15","cited_by_count":51,"area":null},{"id":"2109.02066","title":"Hierarchical Object-to-Zone Graph for Object Navigation","created":"2021-09-05","cited_by_count":34,"area":null},{"id":"2207.10761","title":"TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors","created":"2022-07-21","cited_by_count":30,"area":null},{"id":"2108.02366","title":"Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning","created":"2021-08-05","cited_by_count":27,"area":null},{"id":"2105.10160","title":"Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection","created":"2021-05-21","cited_by_count":22,"area":null},{"id":"2303.06471","title":"Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review","created":"2023-03-11","cited_by_count":20,"area":null},{"id":"2110.07582","title":"Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding","created":"2021-10-14","cited_by_count":19,"area":null},{"id":"2105.01652","title":"The Pursuit of Knowledge: Discovering and Localizing Novel Categories using Dual Memory","created":"2021-05-04","cited_by_count":13,"area":null},{"id":"2105.11866","title":"GraphFM: Graph Factorization Machines for Feature Interaction Modeling","created":"2021-05-25","cited_by_count":13,"area":null},{"id":"2504.05457","title":"Taxonomy-Aware Evaluation of Vision-Language Models","created":"2025-04-07","cited_by_count":11,"area":"mllm"},{"id":"2107.01877","title":"Faster-LTN: a neuro-symbolic, end-to-end object detection architecture","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2107.05869","title":"Applications of knowledge graphs for food science and industry","created":"2021-07-13","cited_by_count":8,"area":null},{"id":"2306.09482","title":"Sample-Efficient Learning of Novel Visual Concepts","created":"2023-06-15","cited_by_count":8,"area":null},{"id":"2106.06307","title":"Survey of Image Based Graph Neural Networks","created":"2021-06-11","cited_by_count":7,"area":null},{"id":"2201.11794","title":"A Survey on Visual Transfer Learning using Knowledge Graphs","created":"2022-01-27","cited_by_count":7,"area":null},{"id":"2203.12949","title":"Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings","created":"2022-03-24","cited_by_count":7,"area":null},{"id":"2104.02962","title":"DyGCN: Dynamic Graph Embedding with Graph Convolutional Network","created":"2021-04-07","cited_by_count":6,"area":null},{"id":"2311.15781","title":"Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs","created":"2023-11-27","cited_by_count":6,"area":null},{"id":"2104.09880","title":"GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing","created":"2021-04-20","cited_by_count":5,"area":null},{"id":"2106.07615","title":"Magic Layouts: Structural Prior for Component Detection in User Interface Designs","created":"2021-06-14","cited_by_count":5,"area":null},{"id":"2206.10090","title":"KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondences","created":"2022-06-21","cited_by_count":5,"area":null},{"id":"2401.16270","title":"Capturing Knowledge Graphs and Rules with Octagon Embeddings","created":"2024-01-29","cited_by_count":5,"area":null},{"id":"2107.13841","title":"Addressing materials' microstructure diversity using transfer learning","created":"2021-07-29","cited_by_count":4,"area":null},{"id":"2109.09063","title":"Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification","created":"2021-09-19","cited_by_count":4,"area":null},{"id":"2203.09121","title":"DRAG: Dynamic Region-Aware GCN for Privacy-Leaking Image Detection","created":"2022-03-17","cited_by_count":4,"area":null},{"id":"2205.00001","title":"Brainish: Formalizing A Multimodal Language for Intelligence and Consciousness","created":"2022-04-14","cited_by_count":4,"area":null},{"id":"2206.12142","title":"ER: Equivariance Regularizer for Knowledge Graph Completion","created":"2022-06-24","cited_by_count":4,"area":null},{"id":"2210.11169","title":"Content-based Graph Privacy Advisor","created":"2022-10-20","cited_by_count":4,"area":null},{"id":"2212.10207","title":"Graph Neural Networks in Computer Vision -- Architectures, Datasets and Common Approaches","created":"2022-12-20","cited_by_count":4,"area":null},{"id":"2302.11082","title":"BB-GCN: A Bi-modal Bridged Graph Convolutional Network for Multi-label Chest X-Ray Recognition","created":"2023-02-22","cited_by_count":4,"area":null},{"id":"2307.00228","title":"InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs","created":"2023-07-01","cited_by_count":4,"area":null},{"id":"2309.05943","title":"Knowledge-Guided Short-Context Action Anticipation in Human-Centric Videos","created":"2023-09-12","cited_by_count":4,"area":null},{"id":"2401.00608","title":"Reviving the Context: Camera Trap Species Classification as Link Prediction on Multimodal Knowledge Graphs","created":"2023-12-31","cited_by_count":4,"area":null},{"id":"2510.04714","title":"Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction","created":"2025-10-06","cited_by_count":4,"area":null},{"id":"2110.00269","title":"A Survey of Knowledge Enhanced Pre-trained Models","created":"2021-10-01","cited_by_count":3,"area":null},{"id":"2204.01450","title":"Learning Commonsense-aware Moment-Text Alignment for Fast Video Temporal Grounding","created":"2022-04-04","cited_by_count":3,"area":null},{"id":"2211.00901","title":"A survey on the development status and application prospects of knowledge graph in smart grids","created":"2022-11-02","cited_by_count":2,"area":null},{"id":"2212.13151","title":"Semantic Enhanced Knowledge Graph for Large-Scale Zero-Shot Learning","created":"2022-12-26","cited_by_count":2,"area":null},{"id":"2303.14322","title":"Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA) for Remote Land-use Change Detection","created":"2023-03-25","cited_by_count":2,"area":null},{"id":"2311.07759","title":"Enabling High-Level Machine Reasoning with Cognitive Neuro-Symbolic Systems","created":"2023-11-13","cited_by_count":2,"area":"lr"},{"id":"2503.12464","title":"Learning Privacy from Visual Entities","created":"2025-03-16","cited_by_count":2,"area":null},{"id":"2509.23373","title":"Graph Your Own Prompt","created":"2025-09-27","cited_by_count":2,"area":null},{"id":"2112.04871","title":"KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings","created":"2021-12-09","cited_by_count":1,"area":null},{"id":"2307.03853","title":"Teach Me How to Learn: A Perspective Review towards User-centered Neuro-symbolic Learning for Robotic Surgical Systems","created":"2023-07-07","cited_by_count":1,"area":null},{"id":"2402.19339","title":"Stitching Gaps: Fusing Situated Perceptual Knowledge with Vision Transformers for High-Level Image Classification","created":"2024-02-29","cited_by_count":1,"area":null},{"id":"2410.13651","title":"Help Me Identify: Is an LLM+VQA System All We Need to Identify Visual Concepts?","created":"2024-10-17","cited_by_count":1,"area":null},{"id":"2508.04260","title":"Segment Any Vehicle: Semantic and Visual Context Driven SAM and A Benchmark","created":"2025-08-06","cited_by_count":1,"area":null},{"id":"2102.08120","title":"Meta-Path-Free Representation Learning on Heterogeneous Networks","created":"2021-02-16","cited_by_count":0,"area":null},{"id":"2102.11132","title":"Wider Vision: Enriching Convolutional Neural Networks via Alignment to External Knowledge Bases","created":"2021-02-22","cited_by_count":0,"area":null},{"id":"2103.15514","title":"Context-aware short-term interest first model for session-based recommendation","created":"2021-03-29","cited_by_count":0,"area":null},{"id":"2110.13892","title":"HR-RCNN: Hierarchical Relational Reasoning for Object Detection","created":"2021-10-26","cited_by_count":0,"area":null},{"id":"2201.08526","title":"Can Machines Generate Personalized Music? A Hybrid Favorite-aware Method for User Preference Music Transfer","created":"2022-01-21","cited_by_count":0,"area":null},{"id":"2202.03188","title":"Knowledge-Integrated Informed AI for National Security","created":"2022-02-04","cited_by_count":0,"area":null},{"id":"2206.03061","title":"Spatial Parsing and Dynamic Temporal Pooling networks for Human-Object Interaction detection","created":"2022-06-07","cited_by_count":0,"area":null},{"id":"2206.13170","title":"Measuring and Improving the Use of Graph Information in Graph Neural Networks","created":"2022-06-27","cited_by_count":0,"area":null},{"id":"2207.00751","title":"Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity","created":"2022-07-02","cited_by_count":0,"area":null},{"id":"2212.12395","title":"Detecting Objects with Context-Likelihood Graphs and Graph Refinement","created":"2022-12-23","cited_by_count":0,"area":null},{"id":"2303.14475","title":"Informed Machine Learning, Centrality, CNN, Relevant Document Detection, Repatriation of Indigenous Human Remains","created":"2023-03-25","cited_by_count":0,"area":null},{"id":"2410.23988","title":"JEMA: A Joint Embedding Framework for Scalable Co-Learning with Multimodal Alignment","created":"2024-10-31","cited_by_count":0,"area":null},{"id":"2503.04570","title":"Meta Learning not to Learn: Robustly Informing Meta-Learning under Nuisance-Varying Families","created":"2025-03-06","cited_by_count":0,"area":null},{"id":"2503.18463","title":"SIT-FER: Integration of Semantic-, Instance-, Text-level Information for Semi-supervised Facial Expression Recognition","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2607.00839","title":"Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}